Predicting dryer maintenance using machine wearables

ABSTRACT

Disclosed is an IoT-based system for overseeing process control and predictive maintenance of a machine or a network of machines by employing machine wearable sensors. The system comprises a plurality of IR temperature sensors, each of which secured to the exterior of the machine; each IR sensor capable of transmitting captured temperature data wirelessly over a communications network, an algorithm engine capable of receiving data from the IR sensors, the algorithm engine for further processing the received data to recognize real-time temperature patterns, deviations, etc., and based on the same issuing control commands pertaining to the machine, and one or more control modules disposed in operative communication with the control panel of the machine, the control module capable of receiving, over a communications network, the control commands and executing the same resulting in accomplishing process control or predictive maintenance of the machine or both.

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This patent application is a 35 USC 120 continuation application of U.S.Ser. No. 14/599,461, now published as United States patent publicationUS 2016-0209831 A1, filed 17 Jan. 2015 in the name of Prophecy Sensors,LLC and entitled “IoT Enabled Process Control and Predictive Maintenanceusing Machine Wearables.”

STATEMENT REGARDING FEDERAL FINANCING RESPECTING THIS INVENTION

Not applicable.

FIELD OF THE INVENTION

The present invention relates to Internet of Things (IoT), moreparticularly, to Machine to Machine (M2M) IoT, and even moreparticularly to an IoT-based system for administering process controland predictive maintenance of machines, such as, dryers, pumps, motors,boilers, etc., using “machine wearables”.

Internet of Things is a network of uniquely-identifiable, purposed“things” that are enabled to communicate data pertaining thereto,therebetween over a communications network whereby, the communicateddata form a basis for manipulating the operation of the “things”. The“thing” in the Internet of Things could virtually be anything that fitsinto a common purpose thereof. For example, a “thing” could be a personwith a heart rate monitor implant, a farm animal with a biochiptransponder, an automobile that has built-in sensors to alert its driverwhen tire pressure is low, or the like, or any other natural or man-madeentity that can be assigned a unique IP address and provided with theability to transfer data over a network. Notably, if all the entities inan IoT are machines, then the IoT is referred to as a Machine to Machine(M2M) IoT or simply, as mentioned earlier, an M2M IoT.

It is apparent from the aforementioned examples that an entity becomes a“thing” of an M2M IoT especially, when the entity is attached with oneor more sensors capable of capturing one or more types of datapertaining thereto: segregating the data (if applicable); selectivelycommunicating each segregation of data to one or more fellow “things”;receiving one or more control commands (or instructions) from one ormore fellow “things” wherein, the one or more control commands is basedon the data received by the one or more fellow “things”; and executingone or more commands resulting in the manipulation or “management” ofthe operation of the corresponding entity. Therefore, in an IoT-enabledsystem, the “things” basically manage themselves without any humanintervention, thus drastically improving the efficiency thereof.

In today's M2M IoT landscape, especially when it comes to the context ofthe employment of temperature sensors within dryer systems, such as, ahopper dryer, they are usually installed within the machines withinspecialized casings so as not to subject them to harsh conditions withinthe machines. In most of the cases, the sensors are also needed to beinstalled at specific locations within a machine, and therefore,sometimes, this leads to the necessity of designing the sensors ofdifferent sizes and shapes so as to fit into its assigned locationseamlessly. Overall, this practice of installing encased sensors withinmachines, not only increases the cost of the machines, but also makes itdifficult to access, replace and maintain them. Further, as wirelesssignals are incapable of being transmitted through the casing andmachine walls, the sensors are physically wired to receivers disposedoutside of the machines. This again leads to the increase of cost andlimits the proximity of the receivers with respect to the machine,thereby complicating the entire IoT setup. Machine wearable sensors thatare easily removably “worn” over the machines may be a solution to theissues of cost and complexity surrounding the IoT.

U.S. Pat. No. 8,726,535 to Garrido et al. discloses a system forcontrolling heated air drying where, exhaust temperature is measuredduring drying and compared to a target or ideal exhaust temperaturefunction or reference. Drying factors are adjusted to compensate for thevariance between measured exhaust temperature and the target or idealexhaust temperature function to influence actual exhaust temperature andto follow the target or ideal exhaust temperature function duringdrying. Drying factors such as inlet air temperature and drying pressurecan be controlled manually or automatically by the above comparison topromote efficient and controlled drying. In this prior art invention,although there is a concept of machines fixing machines, i.e., theconcept of IoT, the role of machine wearables in the scheme of things isnowhere to be seen.

U.S. Pat. No. 7,938,935 to MacHattie et al. teaches measurement of thecondition of paper machine clothing, which involves, by employingInfrared spectroscopy techniques, measuring (i) the moisture level inboth the sheet of wet stock and the papermaking machine clothing onwhich the sheet is supported and (ii) the moisture level in the clothingalone as a separate layer of material. Differential measurement thusyields the moisture content of the sheet of wet stock alone. Changes inthe moisture level in the clothing at the press section can becorrelated with corresponding changes in the quality or physicalproperty of the paper produced. Notably, both fixed point and scanningIR sensors are strategically positioned in the press section to generatemachine direction and/or cross machine direction water profiles forprocess control. Although the prior art, albeit adapted for a differentmachine, teaches process control using IR sensors, the concept ofemploying machine wearables however is non-evident.

U.S. Pub. No. 20070193056 to Switalski discloses a textile dryer capableof monitoring heating chamber temperature (internal thermocouple), peakink temperature (absorption infrared probe at exit), real-time inktemperature (donut thermocouple) as the textile travels through thechamber, and gas consumption is disclosed. A controller permits one toset numerous parameters and view graphs of the monitored variables overtime. Recipes or job settings can be stored for recall and use later. Inaddition, visual and audible warnings and alarms are incorporated intothe system. The prior art also talks about employment of outfeedsensors, which basically is an IR sensor, positioned outside of exitopening above the belt to continuously sense and read the outfeedtemperature of an article emerging from the heating chamber of the dryeron the belt. Although the outfeed sensors lie outside of the dryer, theyclearly are not machine wearables as they do not sense temperaturewithin the dryer from the outside thereof.

U.S. Pat. No. 5,487,225 to Downie discloses an apparatus for controlleddrying of polymer plastic pellets within a dryer hopper. The apparatuscomprises a sensor tree having a plurality of temperature sensors spacedvertically on the tree, which is positioned vertically within the dryerhopper so that the individual sensors are each located at varyingvertical distances from the bottom to the top of the dryer hopper. Atarget temperature for a particular type of polymer plastic pellet, whenmaintained for a specified residence time, indicates that the pellet isthoroughly dry for use in a manufacturing process. By determining thevertical level at which the target temperature has been achieved for thedesired residence time, the amount of dry material within the hopperthat is ready to be input to the manufacturing process is determined. Asignal processing unit operating a software program automaticallycontrols the throughput of the dryer hopper so that only dry polymerplastic pellets leave the hopper. Although some of aspects of thisparticular prior art seem closer to the present invention, such as, thevertical alignment of sensors, the prior art still doesn't read on thepresent invention as the sensors of the prior art are disposed withinthe dryer and thereby are clearly not machine wearables.

It is evident from the discussion of the aforementioned prior art thatnone of them pave way for the reduction of cost and complexity of M2MIoT systems using the concept of machine wearables. There is need in theart for a solution for the aforementioned problem associated with thesensors especially.

SUMMARY

The present invention aims to solve the aforementioned problems byemploying “machine wearable” sensors (which will also be referred to assimply “machine wearables”) in lieu of conventional sensors installedwithin the machine. A machine wearable sensor is advantageouslydifferent from a conventional sensor in that, a machine wearable sensoris “worn” over the machine or, in other words, attached to the exteriorof the machine. The effectiveness with which data is captured by amachine wearable sensor is no inferior compared to that of conventionalsensors. Added to that, machine wearable sensors are readily accessible,thereby making them easier to maintain, replace, etc., which leads tothe conclusion that employment of machine wearables leads to significantreduction of cost, complexity of the IoT setup, while not compromisingon the “effectiveness” aspect as compared to conventional sensors.

The present invention comprises a hopper dryer comprising an elongate,rectangular, vertically-oriented sight glass. In one embodiment, threevertically-aligned and spaced apart infrared (IR) sensors are mounted tothe dryer hopper such that, the IR sensors are positioned to face thesight glass so as to capture the IR radiation passing through the sightglass so as to gauge the temperature within the hopper dryer. Thetemperature data captured by the IR sensors are, over a WirelessPersonal Area Network (WPAN), transmitted to a sensor network.

The sensor network, upon receiving the continuous stream of temperaturedata, is configured to map the same into a pattern in real-time.Depending on whether the pattern is normal or anomalous, the algorithmengine is configured to generate control commands for the hopper dryerthat pertains to either process control or predictive maintenance, orboth. The control commands, over the Internet, are transmitted to thehopper dryer, which executes the same resulting in the process control,predictive maintenance, or both.

Other objects and advantages of the embodiments herein will becomereadily apparent from the following detailed description taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1, according to an embodiment of the present invention, is anillustration of a block diagram of the IoT-based system of the presentinvention.

FIG. 2, according to an embodiment of the present invention, is anotherillustration of a block diagram of the IoT-based system of the presentinvention.

FIG. 3, according to an embodiment of the present invention, is anillustration of an exemplary hopper dryer.

FIG. 4, according to an embodiment of the present invention, is anillustration of a hopper dryer mounted with a machine wearable IRsensor.

FIG. 5, according to an embodiment of the present invention, is anillustration of a sensor network.

FIG. 6, according to an embodiment of the present invention, is anillustration of a block diagram of the algorithm engine.

FIGS. 7A and 7B, according to an embodiment of the present invention,are maps representing normalcy and anomaly respectively.

FIG. 8, according to an alternate embodiment of the present invention,is another illustration of a block diagram of the IoT-based system ofthe present invention.

FIGURES—REFERENCE NUMERALS

-   -   10—IoT-based System    -   12—Machine/Hopper Dryer    -   14—Machine Wearable Sensor/IR Sensor    -   16—WPAN    -   18—Sensor Network    -   20—Internet    -   22—Algorithm Engine    -   24—User Terminal    -   26 f—First Location    -   26 s—Second Location    -   26 t—Third Location    -   28—Mapping Module    -   30—Database    -   32—First Relational Module    -   34—Second Relational Module    -   36—Command Module

DETAILED DESCRIPTION

In the following detailed description, a reference is made to theaccompanying drawings that form a part hereof, and in which the specificembodiments that may be practiced is shown by way of illustration. Theseembodiments are described in sufficient detail to enable those skilledin the art to practice the embodiments and it is to be understood thatthe logical, mechanical and other changes may be made without departingfrom the scope of the embodiments. The following detailed description istherefore not to be taken in a limiting sense.

Referring to FIGS. 1 through 4, the present invention comprises aMachine to Machine (M2M) Internet of Things (IoT)-based system 10 foroverseeing process control and predictive maintenance of a machine 12 byemploying machine wearable sensors 14 (or simply, “machine wearables”).The machine 12 comprises a conventional hopper dryer 12 comprising avertically oriented, elongate, rectangular sight glass 13 wherein, theutility of the sight glass 13, aside from the obvious reason ofmonitoring the dryer 12, will become apparent from the following body oftext. The machine wearable sensors 14 comprise wireless infrared (IR)sensors 14, which are easily removably “worn” over or mounted to theexterior of the dryer 12 as opposed to being installed within the dryer12. More particularly, each IR sensor 14 is magnetically attached orsecured to the exterior of the dryer 12. Even more particularly, each IRsensor 14 is encased in a housing, which is embedded or lined with amagnet wherein, the magnet is about which, the housing (including the IRsensor 14) is secured to the exterior of the dryer 12. In oneembodiment, the housing is mounted to the dryer 12 by means ofcommonplace fasteners such as, screws. Notably, each IR sensor 14 issecured to the dryer 12 such that, the IR sensor 14 interfaces with orcaptures the temperature data from the dryer 12 via the sight glass 13,which allows for the IR radiation within the dryer 12 to passtherethrough. Simply put, each IR sensor is mounted to the dryer 12 suchthat, the IR sensor 14 is positioned to face the sight glass 13 so as tocapture the IR radiation through the sight glass 13. Each IR sensor 14is powered by a power source (such as, a battery) disposed therewithin.In one embodiment, the power source is rechargeable.

Referring to FIGS. 1 through 3, three IR sensors 14 are employed by thesystem 10 wherein, the IR sensors 14, while facing or abutting the sightglass 13, are vertically aligned and spaced apart from one another so asto detect temperature values at three vertically-aligned and verticallyspaced apart locations within a hopper dryer 12 from the outside thereofvia the sight glass 13. As can be appreciated from FIG. 3, the threelocations comprise a first location 26F of the inlet of the dry airflow, a second location 26S of the outlet of the flow, and a thirdlocation 26T disposed preferably midway between the first and secondlocations 26F and 26S. Notably, the first location 26S comprises areturn hose neck location of the hopper dryer 12. In one embodiment, theplurality of locations comprises two locations viz., a first location26F of the inlet of the dry air flow and a second location 26S of theoutlet of the flow. The IR sensors 14 are not only configured to capturetemperature data but also to transmit the captured data over acommunications network.

Referring to FIGS. 1, 2 and 5, the system 10 further comprises a sensornetwork 18 wherein, the sensor network 18 is disposed in operativecommunication with the IR sensors 14 over a communications network. Moreparticularly, the sensor network 18, which preferably comprises a ZigBeeMaster®, is configured to incessantly receive the temperature data fromthe IR sensors 14 in real-time. More particularly, the communicationsnetwork over which, the data is transmitted from the IR sensors 14 tothe sensor network 18 comprises a Wireless Personal Area Network (WPAN)16, which preferably comprises ZigBee®. The sensor network 18, apartfrom receiving the continuous stream of temperature data, is alsoconfigured to continuously transmit the same over a wider communicationsnetwork, viz., the Internet 20, for further processing, which willbecome apparent from the following body of text.

Referring to FIGS. 1 and 2, the system 10 further comprises an algorithmengine 22, which as can appreciated from the referred drawings, isdisposed in operative communication with the sensor network 18, userterminals 24, and the machine 12 preferably over the Internet 20. Thealgorithm engine 22 is preferably run by one or more relational databasealgorithms, the utility of which will become apparent from the followingbody of text. Further, in one embodiment, the algorithms run by thealgorithm engine 22 are of machine learning nature. The algorithm engine22 preferably comprises a distributed Big Data system such as, Hadoop,Storm or Spark. The algorithm engine 22 is configured to receive thestream of data transmitted by the sensor network 18 for furtherprocessing to generate control commands that pertain to either processcontrol or predictive maintenance, or both.

Referring to FIGS. 1, 2, and 6, the algorithm engine 22 comprises amapping module 28, a database 30, a first relational module 32, a secondrelational module 34, and a command module 36. The algorithm engine 22,upon receiving the stream of real-time data from the sensor network 18,is initially received by the mapping module 28, which performs areal-time mapping or pictorially patterning the same using a machinelearning algorithm. The database 30 comprises one or more normaltemperature patterns (or maps) wherein, each normal pattern isassociated with one or more control commands. An exemplary normalpattern is represented by the graph in FIG. 7A. The database 30 alsocomprises one or more anomalous temperature patterns, wherein, eachanomalous pattern is an indication of a malfunction of the machine.Examples of such malfunctions include overheating, clogged filters,motor malfunctioning, etc. An exemplary anomalous pattern is representedby the graph in FIG. 7B. Further, each anomalous pattern within thedatabase 30 is associated with one or more control commands, the utilityof which will become apparent from the following body of text.

Still referring to FIGS. 1, 2, and 6, upon mapping the real-timetemperature data, the pattern of the real-time data is received by thefirst relational module 32, which is configured to compare the sameagainst the normal patterns in the database 30. Upon finding a match asenabled by relational database algorithm, the corresponding controlcommands (if applicable) are transmitted to the control panel of themachine as enabled by the command module 36 over a communicationsnetwork, preferably the Internet 20. The control panel of the machine12, upon receiving the control commands, executes the same resulting inthe process control of the machine 12. On the other hand, if no match isfound by the first relational module 32, meaning that the real-timepattern is an anomalous pattern, the real-time pattern is received bythe second relational module 34, which compares the same against theanomalous patterns in the database 30. Upon finding a match, as enabledby relational database algorithm, the corresponding control commands aretransmitted to the control panel of the machine 12 as enabled by thecommand module 36 over the Internet 20. The control panel, uponreceiving the control commands, executes the same, resulting in thepreventive maintenance of the machine 12.

Referring to FIGS. 1 and 2, the system 10 further comprises a monitoringmodule disposed in operative communication with the algorithm engine 22wherein, the monitoring module, which basically comprises a computerapplication, is accessible from a remote user terminal 24 over theInternet 20. The user terminal 24 could be a smartphone, a tablet PC, alaptop, or the like. The monitoring module enables the users to monitorthe system 10 from remote locations via the user interface of the userterminal 24. The monitoring module is configured to display thepictorial representation of the data received by the algorithm engine 22in real-time and also the control commands transmitted by the algorithmengine 22 in response to the received data.

The aforementioned embodiments are able to be implemented, for example,using a machine-readable medium or article which is able to store aninstruction or a set of instructions that, if executed by a machine,cause the machine to perform a method and/or operations describedherein. Such machine is able to include, for example, any suitableprocessing platform, computing platform, computing device, processingdevice, electronic device, electronic system, computing system,processing system, computer, processor, or the like, and is able to beimplemented using any suitable combination of hardware and/or software.The machine-readable medium or article is able to include, for example,any suitable type of memory unit, memory device, memory article, memorymedium, storage device, storage article, storage medium and/or storageunit; for example, memory, removable or non-removable media, erasable ornon-erasable media, writeable or re-writeable media, digital or analogmedia, hard disk drive, floppy disk, Compact Disk Read Only Memory(CD-ROM), Compact Disk Recordable (CD-R), Compact Disk Re-Writeable(CD-RW), optical disk, magnetic media, various types of DigitalVersatile Disks (DVDs), a tape, a cassette, or the like. Theinstructions is able to include any suitable type of code, for example,source code, compiled code, interpreted code, executable code, staticcode, dynamic code, or the like, and is able to be implemented using anysuitable high-level, low-level, object-oriented, visual, compiled and/orinterpreted programming language, e.g., C, C++, Java, BASIC, Pascal,Fortran, Cobol, assembly language, machine code, or the like. Functions,operations, components and/or features described herein with referenceto one or more embodiments, is able to be combined with, or is able tobe utilized in combination with, one or more other functions,operations, components and/or features described herein with referenceto one or more other embodiments, or vice versa.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the embodiments herein that others can, byapplying current knowledge, readily modify and/or adapt for variousapplications such specific embodiments without departing from thegeneric concept, and, therefore, such adaptations and modificationsshould and are intended to be comprehended within the meaning and rangeof equivalents of the disclosed embodiments. It is to be understood thatthe phraseology or terminology employed herein is for the purpose ofdescription and not of limitation. Therefore, while the embodimentsherein have been described in terms of preferred embodiments, thoseskilled in the art will recognize that the embodiments herein can bepracticed with modification within the spirit and scope of the appendedclaims.

Although the embodiments herein are described with various specificembodiments, it will be obvious for a person skilled in the art topractice the invention with modifications. For example, the machinecould be any machine that is capable of being controlled remotely. Inone embodiment, as shown in FIG. 8, the machine comprises a pump thatemploys wearable temperature and pressure sensors as the hopper dryeremployed temperature sensors. However, all such modifications are deemedto be within the scope of the claims.

The following is claimed:
 1. Apparatus for monitoring process machineoperation and providing prediction-based maintenance of the machine byemploying machine wearable sensors, comprising: (a) a communicationsnetwork; (b) a plurality of machine-wearable infrared temperaturesensors, each secured to the machine; each sensor transmitting capturedtemperature data wirelessly over the communications network; (c) analgorithm engine receiving data from the sensors via the communicationsnetwork, the algorithm engine processing the received data to recognizereal-time temperature patterns and deviations, issuing control commandsbased on the same for operation of the machine; and (d) a control moduleconnected to the control panel of the machine via the communicationsnetwork, the control module receiving, over the communications network,the control commands from the algorithm engine and executing thecommands to control the machine and to provide prediction-basedmaintenance of the machine.